Re: DO NOT BELIEVE IN WHAT Jack Tomsky say

On Jul 17, 8:20 pm, "David L. Wilson" <dwilson...@xxxxxxxxxxx> wrote:
"Jack Tomsky" <jtom...@xxxxxxxxxxxxx> wrote in message

news:26885585.1216142726395.JavaMail.jakarta@xxxxxxxxxxxxxxxxxxxxxxxxx

For several years now, I've been trying to explain to Afonso the basics of
hypothesis testing, but nothing seems to penetrate. I've concluded that
nothing will ever penetrate until he takes a class in Statistics 101.

Although not wishing to join the arguing, I would atleast like to understand
who agrees with what. It is unclear in the post below who, Jack or Afonso,
agrees or disagrees with the statements 1 and 2 below (and similarly in
previous posts). I know the whether the statements below, though not
mathematically rigorous, are true or not, but would like to know separately
simply "yes" or "no" (without arguements) to whether Afonso and Jack agree
or disagree with them. If one agrees with them and the other does not, I
will know what I think of both's knowledge on this subject. If both agree
or disagree with the statements below, then why are we reading them--seems
we need ones where there is diagreement.

DO NOT BELIEVE IN WHAT Jack Tomsky say
From the WEB
__1__"Accepting the null hypothesis" is like
acquitting a defendant. It does NOT prove that the
null hypothesis is true, or that the defendant is
innocent. It means there is a reasonable doubt about
the defendant's guilt. In statistical testing, the
significance level, Type I risk, or alpha risk is the
"reasonable doubt." It is the chance of wrongly
rejecting the null hypothesis when it is true. In
acceptance sampling, it is the producer's risk, or
risk of wrongly rejecting a lot that meets
requirements.
*****************************
And
__2__

HyperStat Online Contents
Why the Null Hypothesis is Not Accepted

A null hypothesis is not accepted just because it is
not rejected. Data not sufficient to show
convincingly that a difference between means is not
zero do not prove that the difference is zero. Such
data may even suggest that the null hypothesis is
false but not be strong enough to make a convincing
case that the null hypothesis is false. For example,
if the probability value were 0.15, then one would
not be ready to present one's case that the null
hypothesis is false to the (properly) skeptical
scientific community. More convincing data would be
needed to do that. However, there would be no basis
to conclude that the null hypothesis is true. It may
or may not be true, there just is not strong enough
evidence to reject it. Not even in cases where there
is no evidence that the null hypothesis is false is
it valid to conclude the null hypothesis is true. If
the null hypothesis is that µ1 - µ2 is zero then the
hypothesis is that the difference is exactly zero. No
experiment can distinguish between the case of no
difference between means and an extremely small
difference between means. If data are consistent with
the null hypothesis, they are also consistent with
other similar hypotheses.

********************************

Luis Amaral Afonso [The moderator ??? destroyer]

I agree. I'm as confused about "who agrees with what" as you are. OMU
.

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